A Shifting Algorithm for Min-Max Tree Partitioning

Becker, Ronald I.; Schach, Stephen R.; Perl, Yehoshua

doi:10.1145/322290.322294

Cited by 63 publications

(16 citation statements)

References 2 publications

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“…There is a minority of cases where the decision about a major superclass is not easy. In such cases, we try to distinguish which of the several superclasses, if any, should have a category-of relationship pointing to it, based on the partial con-(32), (31), (25), (21), (19), (18), (16), (15), (13), (12), and (11).…”

Section: Methodology For Finding a Forest Hierarchymentioning

confidence: 99%

“…hand, if the hierarchical subschema has a forest structure, then there exist efficient algorithms for optimal partitioning according to various criteria [10][11][12][13]. In this paper, we will describe an approach to show that in a hierarchical subschema of a general schema, there exists such a forest hierarchical schema, which helps to support comprehension.…”

Section: Category-of and Role-of Specialization Relationshipsmentioning

confidence: 99%

“…One example of Case 3 is the class ICD9 Diagnostic Procedure (19) which has two definitional superclasses, Diagnostic Procedure (14) and ICD9 (or CPT) Procedure (12). Since both superclasses contribute with equal importance to the class (19), we cannot prefer one over the other.…”

Section: Casementioning

confidence: 99%

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Partitioning an Object-Oriented Terminology Schema

Perl

Halper

et al. 2001

Methods Inf Med

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Abstract:Controlled medical terminologies are increasingly becoming strategic components of various healthcare enterprises. However, the typical medical terminology can be difficult to exploit due to its extensive size and high density. The schema of a medical terminology offered by an object-oriented representation is a valuable tool in providing an abstract view of the terminology, enhancing comprehensibility and making it more usable. However, schemas themselves can be large and unwieldy. We present a methodology for partitioning a medical terminology schema into manageably sized fragments that promote increased comprehension. Our methodology has a refinement process for the subclass hierarchy of the terminology schema. The methodology is carried out by a medical domain expert in conjunction with a computer. The expert is guided by a set of three modeling rules, which guarantee that the resulting partitioned schema consists of a forest of trees. This makes it easier to understand and consequently use the medical terminology. The application of our methodology to the schema of the Medical Entities Dictionary (MED) is presented.

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Section: Methodology For Finding a Forest Hierarchymentioning

confidence: 99%

Section: Category-of and Role-of Specialization Relationshipsmentioning

confidence: 99%

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Partitioning an Object-Oriented Terminology Schema

Perl

Halper

et al. 2001

Methods Inf Med

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“…As soon as the bipartite matching algorithm has been executed, we partition the lattice into a set of k sub-trees using the min-max algorithm proposed by Becker, Schach and Perl [2]. The original algorithm is modified slightly since it was designed to work on a graph whose costs were assigned to the nodes, rather than the edges.…”

Section: Min-max Partitioningmentioning

confidence: 99%

Coarse Grained Parallel On-Line Analytical Processing (OLAP) for Data Mining

Dehne

Eavis

Rau-Chaplin

2001

Computational Science - ICCS 2001

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We study the applicability of coarse grained parallel computing model (CGM) to on-line analytical processing (OLAP) for data mining. We present a general framework for the CGM which allows for the efficient parallelization of existing data cube construction algorithms for OLAP. Experimental data indicate that our approach yield optimal speedup, even when run on a simple processor cluster connected via a standard switch.

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“…In this section, we describe the parallel PipeSort algorithm proposed in [19]. As The k-min-max partitioning problem has been studied in [12,20,11]. The Min-Max shifting algorithm is presented in Algorithm 8, which is based the Min-Max Shifting Algorithm described in [12].…”

Section: P Arallel P Ip E S O R Tmentioning

confidence: 99%

Parallel computation of data cubes

Xin-rong¹

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A Shifting Algorithm for Min-Max Tree Partitioning

Cited by 63 publications

References 2 publications

Partitioning an Object-Oriented Terminology Schema

Partitioning an Object-Oriented Terminology Schema

Coarse Grained Parallel On-Line Analytical Processing (OLAP) for Data Mining

Parallel computation of data cubes

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